The composition and architecture of the extracellular matrix (ECM) defines the metastatic outcome of tumor cells, specifically whether a tumor cell will transition from a non-invasive to an invasive phenotype. However, the extracellular biomolecules responsible are largely unknown. Identifying and understanding the role of specific ECM proteins and modifications involved in tumor progression requires a more comprehensive and precise characterization of ECM within tumor microenvironments. ECM proteins are often covalently cross-linked rendering them resistant to solubilization and proteolytic cleavage. As a result, analyses of tissue samples by traditional proteomic techniques fail to reflect actual protein composition. Lack of suitable sample preparation and quantification methods for accurate molecular characterization of ECM remains a major barrier to progress in the field. The focus of this R33 application is on development and validation of methods to identify and quantify ECM proteins and crosslinked peptides that differ between matrices that support or suppress tumorigenic events. We have made considerable progress towards the goals outlined in our Sample Preparation Methods for the Detailed Characterization of Tumor Associated Extracellular Matrix R21 grant. The highlights of this work involves 1) development of cell culture models for evaluating ECM driven phenotypes, 2) defining a robust ECM extraction protocol that minimizes cellular contamination and permits proteomic analysis of both the strong chaotrope soluble and insoluble ECM fractions, and 3) application of a label- free relative-quantification approach for estimation of protein abundance changes. Ultimately, this work has yielded a proteomic method that results in a more accurate representation of tissue protein composition compared to all others tested. The work proposed in this R33 extension grant builds on these advancements by providing the methods necessary for in-depth characterization of ECM during tumor progression to deliver previously unobtainable molecular detail of cellular microenvironment remodeling events. To facilitate absolute quantification we have developed a library of stable isotope labeled reporter peptides that provide a sensitive proxy for ECM proteins. We will generate additional peptides for fibrillar collagens that contain hydroxyproline residues so that these heavy-labeled libraries can be added to ECM samples of interest for protein quantification. This approach will allow for higher- throughput analysis, improved sensitivity, accuracy, and intra- and inter- sample comparison of protein levels. We will generate a crosslinked-peptide identification strategy to characterize the types and sites of lysyl oxidase (LOX) mediated crosslinks that correlate with tumor progression. The method involves mixed affinity labeling of proteolytic peptides followed by tandem affinity purification for selective crosslinked peptide enrichment. The method will initially be developed using control proteins and tissues, and then applied to tissues from our cancer model and control mice treated +/- LOX inhibitor. Finally, we will examine alterations in ECM composition and crosslinking between pre-neoplastic lesions, early stage, and late stage tumors by applying a stable isotope pulse labeling approach in conjunction with or internal standard peptide library. A 30 day pulse labeling provided by stable isotope Lys containing chow will allow for measurements of new protein incorporated into the ECM of mouse tissue and tumors. Protein abundance and degradation differences between time points will be accounted for using the Arg containing subset of our reporter peptides. These experiments should allow us to obtain molecular resolution, previously unattainable, of the dynamic and reciprocal relationship between ECM deposition, processing and degradation that occur during tumor progression. The development of the proposed methods for absolute quantification and validation of these ECM specific techniques will advance our ability to explore and characterize the role of the ECM in cancer progression. The methods will help investigators understand a poorly understood area of basic biology, cancer progression, and fibrotic diseases in general. Findings in this historically overlooked area are likely to provide paradigm shifts in our understanding of these diseases and the types of proteins considered for therapeutic targeting, and as sources of diagnostic markers. These studies will provide important reagents (reporter peptide library plasmids and SIL-PTM peptides) and resources (protocols and datasets) necessary to move this field toward its ultimate goal of enabling discoveries that improve patients' lives.